147247 20260217205540.0 doi 10.1115/1.4066791 sideral 141080 ART-2024-141080 eng Michopoulos, John G. Special issue: scientific machine learning for manufacturing processes and material systems 2024 Access copy available to the general public Unrestricted Computational modeling, simulation, and optimization of manufacturing processes and materials systems have been a persistent endeavor of the engineering research community at large. Significant progress has been achieved in this field due to the exponential increase in computing power, and the incorporation of data-driven modeling methods. Process and systems modeling often involves expensive and time-intensive simulations and experiments. Incorporation of machine-learning (ML) models as efficient surrogate models has been proven to enhance the human understanding of the behavior of the system at hand and reduce the computational optimization cost of the concerned processes and systems. However, there is a rising need to go beyond the conventional data-driven techniques to address challenges, such as presence of noise in data, limited budget, data sparsity, lack of interpretability of ML models, etc. Tackling these issues will enable more comprehensive modeling of manufacturing processes and discovery of novel material systems. info:eu-repo/semantics/openAccess All rights reserved http://www.europeana.eu/rights/rr-f/ 3.3 2024 ENGINEERING, MANUFACTURING 33 / 71 = 0.465 2024 Q2 T2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS 76 / 177 = 0.429 2024 Q2 T2 0.788 2024 Industrial and Manufacturing Engineering 2024 Q1 Computer Graphics and Computer-Aided Design 2024 Q1 Software 2024 Q2 Computer Science Applications 2024 Q2 6.5 2024 info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion Bhaduri, Anindya Chinesta, Francisco Cueto, Elías Universidad de Zaragoza (orcid)0000-0003-1017-4381 Liu, Dehao Ravi, Sandipp Krishnan Wang, Jian-Xun 5004 605 Universidad de Zaragoza Dpto. Ingeniería Mecánica Área Mec.Med.Cont. y Teor.Est. 24, 11 (2024), 110301 [3 p.] J. Comput. Inf. Sci. Eng. JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING 1530-9827 126905 http://zaguan.unizar.es/record/147247/files/texto_completo.pdf Postprint 2404179 http://zaguan.unizar.es/record/147247/files/texto_completo.jpg?subformat=icon icon Postprint oai:zaguan.unizar.es:147247 articulos driver 2026-02-17-20:36:00 ARTICLE